Intelligent on-line fault tolerant control for unanticipated catastrophic failures

As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.     

Attitude maneuver control of flexible spacecraft by observer-based tracking control

A constraint equation-based control law design for large angle attitude maneuvers of flexible spacecraft is addressed in this paper. The tip displacement of the flexible spacecraft model is prescribed in the form of a constraint equation. The controller design is attempted in the way that the constraint equation is satisfied throughout the maneuver. The constraint equation leads to a two-point boundary value problem which needs backward and forward solution techniques to satisfy terminal constraints. An observer-based tracking control law takes the constraint equation as the input to the dynamic observer. The observer state is used in conjunction with the state feedback control law to have the actual system follow the observer dynamics. The observer-based tracking control law eventually turns into a stabilized system with inherent nature of robustness and disturbance rejection in LQR type control laws.     

复合滑模控制在精密PMLSM激光切割运动平台的应用

针对永磁直线同步电机激光切割运动平台的位置伺服控制低抖振、高精度、强鲁棒的要求,在传统双幂次滑模趋近律的基础上,提出一种变边界层的双幂次滑模趋近律带滑模扰动观测器的复合趋近律滑摸控制方法。变边界层方法是对控制系统的控制精度要求和降低抖振的权衡,而所提出的方法又继承了传统双幂次滑模趋近律方法的有限时间收敛特性。为了降低控制系统设计的保守性,设计了一种基于超螺旋算法的滑模扰动观测器对系统的未知扰动进行估计,并在此算法中添加一个幂指数,通过仿真实验证明了提高幂指数的数值可加快未知扰动的估计值的收敛速度。结合Lyapunov稳定性理论,证明了闭环系统的稳定性。最后,搭建了用于激光切割的永磁直线同步电机平移试验台对所提出的控制器进行测试。实验结果表明:本文所提出的控制器的位置跟踪误差不超过1μm,且误差波动较小,能够满足伺服控制系统的要求。     

A robust algorithm for a class of optimal control problems subject to regional stability constraints and disturbances

A robust globally convergent algorithm for solving the optimization control problem (OCP) in both state feedback controller and observation control system is investigated. Finding the OCP adjoint parameter for computing the optimal observer gain and feedback gain vectors are desired. First, the optimal control problem considering stability of degree constrains and disturbance that affects the dynamics of system is converted into a two-point boundary value problem (TPBVP). Then, we apply the He’s polynomials based on homotopy perturbation method (HPM) as an efficient method to find both optimal gains. The algorithm will be modified do decrease the number of iterations required to attain a desired control problem cost function. As a result lower computational complexity is required when compared with other state of the art methods. Applying the HPM makes the solution procedure become easier, simpler and more straightforward. In the proposed method the control problem can be solved with lower amplitudes of the input signal (control effort), comparing with analytical method. Lower control efforts may also help to avoid saturation effects, and to restrain the system to work within linear operating areas of the state space. On the other hand, there is a tradeoff between control effort and the degree of optimality obtained. For demonstrating the simplicity and efficiency of the proposed optimal control method, the algorithm is compared with a control architecture using the Kalman filter estimator and a controller gain designed by the Lyapunov’s second method.     

Generalized Discrete-time nonlinear disturbance observer based fuzzy model predictive control for boiler–turbine systems

The boiler–turbine system (BTS) is usually subject to the tight input constraint, the strong nonlinearity and the complex disturbance, which makes the control a challenging task To this end, a disturbance observer based fuzzy model predictive control (DOBFMPC) scheme is proposed for the BTS in this paper. The generalized discrete-time nonlinear disturbance observer (GDNDO) is first developed to estimate the higher-order disturbance by systematically extending the conventional nonlinear disturbance observer. The GDNDO exhibits a series structure of the internal states, and can precisely estimate the disturbance if its order is equal to or greater than that of the disturbance In addition, a baseline fuzzy model predictive control (FMPC) law is synthesized on the fuzzy model. With FMPC, the asymptotic stability is guaranteed, and meanwhile the input constraints are satisfied by both the free control variables and the future control inputs in the form of the state feedback law. At last, the disturbance estimate and the FMPC are applied to constitute the DOBFMPC law. With the proper design of the disturbance compensation gain, the disturbance influence is removed from the output channels by the composite DOBFMPC law at the steady state. Simulations for a 300 MW subcritical BTS well demonstrate the effectiveness of the proposed control scheme.     

Improved adaptive integral line-of-sight guidance law and adaptive fuzzy path following control for underactuated MSV

This paper presents an adaptive fuzzy path following control law based on an improved adaptive integral line-of-sight (IAILOS) guidance law for the underactuated marine surface vessel (MSV) exposed to the time-varying ocean currents and time-varying sideslip angle. Initially, the IAILOS guidance law is proposed which can not only calculate the desired yaw angle but also estimate the time-varying ocean currents and time-varying sideslip angle simultaneously. Furthermore, the adaptive fuzzy path following control law is established by combining with the estimator to cope with the MSV’s attitude tracking control and velocity tracing control problem via backstepping technique. Specifically, the dynamic uncertainties and unknown environment disturbances are compensated by the fuzzy logic system with fuzzy updating law based on estimation error rather than tracking error. Additionally, two high-order tracking differentiators (TDs) are designed to construct derivatives of virtual control vector and reduce computational complexity inherent in backstepping method. It is proved that the proposed adaptive fuzzy path following control law can drive the vessel to track the desired path and tracking error can converge to an arbitrarily small compact set, while guaranteeing all signals in the closed-loop control system are uniformly ultimately bounded. Finally, simulation results and comparisons are carried out to demonstrate the effectiveness of the proposed control approach.     

一类多缸液压机的分散滑模控制

通过对一类锻造液压机的分析,在考虑多缸耦合情况下为其建立了非线性系统数学模型.将该模型视为非线性关联大系统,且将其转化为可控正则型,提出采用分散滑模控制理论对其进行滑模变结构控制.针对模型转换后控制方程中状态量与控制量同时具有关联性的特点,提出通过模拟求解一个多元一次方程组的方法,得到了基于指数趋近律的分散滑模控制律,有效解决了多缸耦合情况下控制律难于求解的问题.仿真结果表明,所设计的控制器使系统实现了高精度的位置跟踪,获得了较强的抗扰性,控制效果良好,且所提方法思路清晰,为同类模型的控制方案提供了参考.     

基于边界特征尺度匹配延拓的EMD改进方法及应用

针对经验模态分解(empirical mode decomposition,EMD)中存在的端点效应问题,提出一种边界局部特征尺度延拓的EMD改进方法。通过计算信号边缘处与信号内部任何一段子波的匹配误差,确定信号的规律性强弱。在信号内在规律性较强的情况下,进行内在的匹配波形延拓,最大限度地维护信号的内在趋势;在信号规律性较弱的情况下,特别是信号边缘发生异常变化的情况下,只考虑边缘处的局部信息,根据边缘局部极值点的特征进行延拓,对延拓的极值点序列进行包络拟合,估计出均值曲线。该方法保证了信号有效数据的正确分解,提高了信号的分解精度,实现了EMD算法的改进。仿真实验验证了该方法能较好地抑制EMD端点效应。     

Performance optimization of linear active disturbance rejection control approach by modified bat inspired algorithm for single area load frequency control concerning high wind power penetration

The linear active disturbance approach is employed to deal with the load frequency control issue of a single area wind power system based on doubly fed induction generator, and the performance of the control law is optimized by using the bat-inspired algorithm. The load frequency control issue has become more challenging in a complex power system based on wind energy conversion system due to the varying feature of the wind penetration, and sustaining the balance between the power generation and demand by rejecting the internal uncertainties in the process model and the external disturbances simultaneously. In the framework of the presented linear active disturbance rejection control approach, by constructing an extended state observer, the total disturbance, including all the unmodelled dynamics in the process model and the external disturbances, can be estimated in real time and then compensated by a simple linear PD control law. The controller parameters tuning is then simplified into the optimization of the two bandwidths: observer bandwidth, and the controller bandwidth. Then, this issue can be achieved by employing the heuristic modified bat inspired algorithm based on the optimization of the proposed performance index. The effectiveness of the proposed approach is validated by the extensive simulation examples of the load frequency control issue involved in the single area power system, taking into account different wind penetration, as well as the external disturbances. The performance robustness of the proposed approach against the parameters perturbation in the process model is also demonstrated via the Monte-Carlo method. The performance superiority of the proposed approach over the conventional Proportional Integral and Fuzzy-Proportional Integral based controller even in the presence of external disturbances and uncertainty in power system parameters under different cases of high wind penetration is also validated from the simulation results.     

ADAPTIVE VARIABLE STRUCTURE CONTROLLERS AND APPLICATION TO ENGINE IDLE SPEED CONTROL SIMULATION

A neural-network-based adaptive variable structure control methodology is proposed for the tracking problem of nonlinear discrete-time input-output systems. The unknown dynamics of the system are approximated via radial basis function neural networks. The control law is based on sliding modes and simple to implement. The discrete-time adaptive law for tuning the weight of neural networks is presented using the adaptive filtering algorithm with residue upper-bound compensation. The application of the proposed controller to engine idle speed control design is discussed. The results indicate the validation and effectiveness of this approach.     

High precision tracking control of a servo gantry with dynamic friction compensation

This paper is concerned with the tracking control problem of a voice coil motor (VCM) actuated servo gantry system. By utilizing an adaptive control technique combined with a sliding mode approach, an adaptive sliding mode control (ASMC) law with friction compensation scheme is proposed in presence of both frictions and external disturbances. Based on the LuGre dynamic friction model, a dual-observer structure is used to estimate the unmeasurable friction state, and an adaptive control law is synthesized to effectively handle the unknown friction model parameters as well as the bound of the disturbances. Moreover, the proposed control law is also implemented on a VCM servo gantry system for motion tracking. Simulations and experimental results demonstrate good tracking performance, which outperform traditional control approaches.     

磁悬浮控制力矩陀螺高速转子的高精度位置控制

在受到陀螺效应、动框架效应等影响后产生的磁力非线性问题是磁悬浮控制力矩陀螺(MSCMG)高速转子位置精度下降的主要因素。为解决以上问题,提高转子位置精度,本文分析了转子所受磁力的特性,建立了转子系统非线性动力学模型,提出了神经网络滑模控制方法。设计滑模控制律,采用径向基函数神经网络逼近控制律中的非线性模型,自适应算法根据误差在线调整神经网络的权值,同时可以保证整个系统的稳定性。仿真和实验结果表明,所提出方法的转子位置精度达到99%,稳态误差为0.000 2 mm。神经网络滑模控制可以实现MSCMG转子系统的高精度位置控制。     

Global fast dynamic terminal sliding mode control for a quadrotor UAV

A control method based on global fast dynamic terminal sliding mode control (TSMC) technique is proposed to design the flight controller for performing the finite-time position and attitude tracking control of a small quadrotor UAV. Firstly, the dynamic model of the quadrotor is divided into two subsystems, i.e., a fully actuated subsystem and an underactuated subsystem. Secondly, the dynamic flight controllers of the quadrotor are formulated based on global fast dynamic TSMC, which is able to guarantee that the position and velocity tracking errors of all system state variables converge to zero in finite-time. Moreover, the global fast dynamic TSMC is also able to eliminate the chattering phenomenon caused by the switching control action and realize the high precision performance. In addition, the stabilities of two subsystems are demonstrated by Lyapunov theory, respectively. Lastly, the simulation results are given to illustrate the effectiveness and robustness of the proposed control method in the presence of external disturbances.     

Posture adaptive control of the flexible grinding head for blisk manufacturing

In order to improve the machining quality, stability, consistency, and other mechanical properties of the blisk surface, a novel pneumatic flexible grinding head is designed, and working principle, accessible region, and real-time position of the grinding head are analyzed. Considering the influence of nonlinear dead-zone, unknown system function, and uncertain disturbance on the performance of pneumatic servo system, an adaptive sliding mode control (ASMC) based on extended state observer (ESO) is proposed. ESO is employed to estimate the system state variables and an adaptive law is adopted to compensate the input dead-zone. Finally, stability of the closed-loop system is guaranteed by Lyapunov theory. Experimental results illustrate the perfect estimation of ESO, and the proposed ASMC has much stronger anti-interference and robustness compared with the traditional PID control, which can achieve the control precision within submicron. Grinding experiments show that this method can reduce waviness and roughness of the blade surface by nearly 50 %, and decrease the form error by about 22.93 %.     

基于改进自适应趋近律的弹丸协调臂滑模控制

针对某火炮弹丸协调臂电液伺服系统在传统滑模控制趋近律下存在抖振现象,收敛速度慢等问题,提出一种基于改进自适应趋近律的弹丸协调臂滑模控制。当系统状态变量距离切换面较远的时候,幂次项起主要作用;当系统状态变量距离切换面较近时,自适应变速项起主要作用,随着状态变量变化自适应调节变速项系数,直到状态变量收敛到稳定点。当系统存在参数不确定性和外界扰动时,滑模状态变量可在有限时间收敛到边界层宽度为2.6的稳定误差界内。仿真结果表明,控制策略能有效提高系统的动态精度和到位精度,提高系统的鲁棒性。     

基于摩擦模型的反演滑模控制在大型望远镜上的应用

根据永磁同步电机驱动的大型望远镜转台对指向精度与低速跟踪精度的要求,设计了基于摩擦模型的反演滑模控制器。建立了基于摩擦模型与外部扰动的系统模型;然后,按照反演设计方法,设计了离控制输入最远的子系统,在设计过程中加入滑模控制,从而减小非线性摩擦因素与外部风载等对指向精度与跟踪精度的影响。通过理论仿真和实验研究验证了该方法的有效性。结果显示:所设计的反演滑模控制器具有较好的动态响应,对扰动等不确定性因素具有较强的鲁棒性,当位置阶跃指令为4.6″时,稳态误差为0.048 51″,比传统的PI控制算法减小21.4%;当输入斜率为5(″)/s的位置斜坡指令时,稳态跟踪误差为0.031 26″,比传统的PI控制算法减小30.1%。结果表明提出的方法能够提高望远镜控制系统的指向精度和低速跟踪精度。     

H∞ non-fragile observer-based dynamic event-triggered sliding mode control for nonlinear networked systems with sensor saturation and dead-zone input

This paper considers the problem of robust non-fragile observer-based dynamic event-triggered sliding mode control (SMC) for a class of discrete-time Lipschitz nonlinear networked control systems subject to sensor saturation and dead-zone input nonlinearity. First, an improved dynamic event-triggered scheme (DETS) in consideration of sensor saturation is proposed to reduce the number of data transmission. Next, a non-fragile observer is designed to estimate the system state, which facilitates the construction of the discrete sliding surface. By using a reformulated Lipschitz property, the error dynamics and sliding mode dynamics are modeled as a unified linear parameter varying (LPV) networked system with time-varying delays. Then, based on this model, sufficient conditions are established to guarantee the resulting closed-loop system to be asymptotically stable with a given disturbance attenuation level. Furthermore, an observer-based event-triggered SMC law is designed to drive the trajectories of the observer system onto a region near equilibrium point in a finite time in the presence of dead-zone input nonlinearity. Finally, two practical examples are employed to demonstrate the effectiveness of the proposed method.     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

基于谐波小波包和BSA优化LS-SVM的铣刀磨损状态识别研究

针对铣削刀具磨损状态识别问题,提出谐波小波包和最小二乘支持向量机（LS-SVM）的状态识别方法。为克服传统小波包分解的频带交叠问题,采用谐波小波包提取不同磨损状态下铣削力信号的各频段信号能量,归一化处理后,输入LS-SVM多类分类器,实现铣削刀具磨损状态的识别。针对LS-SVM的惩罚因子和核参数对模型识别精度影响较大的问题,提出回溯搜索算法（BSA）进行自动参数寻优。实验结果表明,谐波小波包比小波包在刀具磨损状态特征提取时具有更好的识别效果。与粒子群算法进行比较,证明BSA优化LS-SVM具有更高的识别精度。     

Control design for one-sided Lipschitz nonlinear differential inclusions

This paper considers stabilization and signal tracking control for one-sided Lipschitz nonlinear differential inclusions (NDIs). Sufficient conditions for exponential stabilization for the closed-loop system are given based on linear matrix inequality theory. Further, the design method is extended to signal tracking control for one-sided Lipschitz NDIs. A control law is designed such that the state of the closed-loop system asymptotically tracks the reference signal. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design technique.